CLUSTERING FRAGMEN METAGENOM MENGGUNAKAN METODE GROWING SELF ORGANIZING MAP (GSOM) ( Studi Kasus Dinas Lingkungan Hidup Kota Jayapura)

N. Banyal, S. Surianti
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Abstract

Metagenome is a microorganism that is taken directly from nature. The sequencen process of metagenome results in the mixing of various organisms. The data collection method used was Observation, using a direct plunge technique to the Jayapura City Environmental Department. This study uses data from metagenome fragments of 300 microbes. The technique of collecting metagenome fragment data used is cluster sampling. The research location is at the Jayapura City Environmental Agency. The purpose of this study is to analyze the effectiveness and efficiency of the Growing Self Organizing Map method in large-scale microbial grouping with short fragment lengths based on oligonucleotide frequencies. For feature extraction, k-mer frequency and spaced are used. Short fragments are used because in previous studies, the length of the fragment used was a long fragment (≥ 8 kbp), so in this study we want to overcome the drawbacks of using short fragments in the grouping of metagenome fragments. The results of the grouping of metagenome fragments will be tested for effectiveness and efficiency.
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聚类FRAGMEN元基因组提供的方法生长自映射组织(GSOM)
宏基因组是一种直接取自自然界的微生物。宏基因组的测序过程导致了多种生物的混合。使用的数据收集方法是观测,使用直接跳入技术到查亚普拉市环境部门。这项研究使用了300种微生物宏基因组片段的数据。收集宏基因组片段数据的技术是聚类抽样。研究地点在查亚普拉市环境局。本研究的目的是分析生长自组织图谱方法在基于寡核苷酸频率的短片段长度微生物大规模分组中的有效性和效率。对于特征提取,使用k-mer频率和间隔。使用短片段是因为在以往的研究中,使用的片段长度为长片段(≥8 kbp),因此在本研究中我们希望克服使用短片段进行宏基因组片段分组的缺点。宏基因组片段分组的结果将检验其有效性和效率。
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